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Remote Sens. 2018, 10(9), 1338; https://doi.org/10.3390/rs10091338

A Forest Attribute Mapping Framework: A Pilot Study in a Northern Boreal Forest, Northwest Territories, Canada

1
Department of Geography, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
2
Natural Resources Canada–Canadian Forest Service, Northern Forestry Centre, Edmonton, AB T6H 3S5, Canada
3
Natural Resources Canada–Canadian Forest Service, Laurentian Forestry Centre, Quebec, QC G1V 4C7, Canada
4
Department of Geography, University of Hawaii at Mānoa, Honolulu, HI 96822, USA
*
Author to whom correspondence should be addressed.
Received: 5 June 2018 / Revised: 10 August 2018 / Accepted: 18 August 2018 / Published: 22 August 2018
(This article belongs to the Special Issue Advances in Remote Sensing of Forest Structure and Applications)
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Abstract

A methods framework is presented that utilizes field plots, airborne light detection and ranging (LiDAR), and spaceborne Geoscience Laser Altimeter System (GLAS) data to estimate forest attributes over a 20 Mha area in Northern Canada. The framework was implemented to scale up forest attribute models from field data to intersecting airborne LiDAR data, and then to GLAS footprints. GLAS data were sequentially filtered and submitted to the k-nearest neighbour (k-NN) imputation algorithm to yield regional estimates of stand height and crown closure at a 30 m resolution. Resulting outputs were assessed against independent airborne LiDAR data to evaluate regional estimates of stand height (mean difference = −1 m, RMSE = 5 m) and crown closure (mean difference = −5%, RMSE = 9%). Additional assessments were performed as a function of dominant vegetation type and ecoregion to further evaluate regional products. These attributes form the primary descriptive structure attributes that are typical of forest inventory mapping programs, and provide insight into how they can be derived in northern boreal regions where field information and physical access is often limited. View Full-Text
Keywords: LiDAR; GLAS; k-NN; forest resource inventory LiDAR; GLAS; k-NN; forest resource inventory
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Mahoney, C.; Hall, R.J.; Hopkinson, C.; Filiatrault, M.; Beaudoin, A.; Chen, Q. A Forest Attribute Mapping Framework: A Pilot Study in a Northern Boreal Forest, Northwest Territories, Canada. Remote Sens. 2018, 10, 1338.

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